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Influence of maternal and fetal factors on fetal magnetocardiography measurements using optically pumped
Alberto Ramirez1, Eric R Siegel2, Amna Qasim3
1Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Background:
Fetal magnetocardiography (fMCG) noninvasively measures the magnetic fields generated by the fetal heart to assess cardiac electrophysiology. The advent of optically pumped magnetometers (OPMs) enables portable, cryogen-free acquisition of high-fidelity fMCG signals. However, maternal and fetal characteristics may introduce variability affecting signal quality and cardiac time-interval (CTI) detectability.
Objective:
This study quantifies the influence of maternal and fetal parameters (placental position, body mass index, fetal heart distance, and gestational age [GA]) on the signal-to-noise ratio (SNR) and CTI detectability in OPM-based fMCG recordings.
Methods:
A total of 107 OPM recordings were obtained longitudinally from 32 pregnant participants (28-38 weeks of gestation) using a bed-based, stand-alone OPM array system. SNR was derived from fMCG signals, and maternal and fetal characteristics were obtained from clinical data. Mixed-effects linear and logistic regression models were used to evaluate associations among these parameters, SNR, and CTI detectability.
Results:
Mean SNR and variance were 10.95 dB and 14.56 dB2, respectively. Multivariable mixed-effects linear regression reduced total variance to 12.55 dB2 and yielded a fixed-effects R2 of 19.8%. SNR increased significantly with GA and decreased with fetal heart distance. Higher SNR was associated with improved CTI detectability, particularly for T wave and QT interval. GA remained a significant predictor of T-wave detectability, whereas fetal heart distance exerted an independent negative effect.
Conclusion:
Fetal heart distance and GA are the primary determinants of OPM-fMCG signal quality. Accounting for maternal physiological variability is essential for optimizing acquisition protocols and improving the interpretability of fetal cardiac data.
